Distribution Information Based Intuitionistic Fuzzy Clustering for Infrared Ship Segmentation

This paper presents a distribution information based intuitionistic fuzzy clustering method for infrared ship segmentation. The algorithm could effectively suppress the influences of nontarget objects with high intensity and intensity inhomogeneity in the infrared ship images. There are mainly two improvements in this paper. First, it proposes a fuzzy clustering algorithm incorporating global distribution information of ship targets in the form of the Gaussian model. The spatial information, along with intensity, is used to exert different effects on different classes. Second, an intuitionistic fuzzy clustering way is incorporated into the process of ship segmentation, which combines the intensity distribution information of the local region. The intuitionistic fuzzy distance and local intensity distribution information would help in solving the problem of intensity inhomogeneity and blurring edges. Experiment results on the dataset containing 200 infrared ship images indicate the superiority of the proposed method compared with other state-of-the-art methods.